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import log from "loglevel";
import { ResponseFormat } from "./openai_api_protocols";
import { LogitProcessor, InitProgressCallback, LogLevel } from "./types";
import {
DependencyError,
InvalidNumberStringError,
MinValueError,
NonNegativeError,
RangeError,
} from "./error";
import { ModelIntegrity } from "./integrity";
/**
* Conversation template config
*/
export interface ConvTemplateConfig {
system_template: string;
system_message: string;
roles: Record<Role, string>;
role_templates?: Partial<Record<Role, string>>;
seps: Array<string>;
role_content_sep?: string;
role_empty_sep?: string;
stop_str: Array<string>;
system_prefix_token_ids?: Array<number>;
stop_token_ids: Array<number>;
add_role_after_system_message?: boolean;
render_empty_system_message?: boolean;
}
/**
* Common vision model config fields. Model-specific fields are accessed
* via the Record<string, unknown> extension.
*/
export type VisionModelConfig = {
mm_tokens_per_image?: number;
boi_token_index?: number;
eoi_token_index?: number;
vision_start_token_id?: number;
vision_end_token_id?: number;
};
export enum Role {
user = "user",
assistant = "assistant",
tool = "tool",
}
export const DefaultLogLevel: LogLevel = "WARN";
/**
* Place holders that can be used in role templates.
* For example, a role template of
* `<<question>> ${MessagePlaceholders.USER} <<function>> ${MessagePlaceholders.FUNCTION}`
* will insert the user message to ${MessagePlaceholders.USER}
* and insert the function message to ${MessagePlaceholders.FUNCTION}
* at run time.
*/
export enum MessagePlaceholders {
system = "{system_message}",
user = "{user_message}",
assistant = "{assistant_message}",
tool = "{tool_message}",
function = "{function_string}",
hermes_tools = "{hermes_tools}",
}
/**
* Information about the tokenizer. Currently, only `token_postproc_method` is used to
* post process the token table when using grammar.
*/
export interface TokenizerInfo {
token_postproc_method: string;
prepend_space_in_encode: boolean;
strip_space_in_decode: boolean;
}
/**
* Config of one chat model, a data structure representing `mlc-chat-config.json`.
* This only corresponds to the chat-related fields and `tokenizer_files` of `mlc-chat-config.json`.
* Only these fields affect the conversation in runtime.
* i.e. The third part in https://llm.mlc.ai/docs/get_started/mlc_chat_config.html.
*
* This is initialized in `MLCEngine.reload()` with the model's `mlc-chat-config.json`.
*/
export interface ChatConfig {
// First three fields affect the entire conversation, i.e. used in `MLCEngine.reload()`
tokenizer_files: Array<string>;
tokenizer_info?: TokenizerInfo;
token_table_postproc_method?: string; // TODO: backward compatibility, remove soon
vocab_size: number;
conv_config?: Partial<ConvTemplateConfig>;
conv_template: ConvTemplateConfig;
// KVCache settings
context_window_size: number;
sliding_window_size: number;
attention_sink_size: number;
// RNNState settings (for hybrid/recurrent models). If unspecified, runtime picks a safe default.
max_history_size?: number;
// Fields below can be swapped per-generation via `GenerationConfig`
// Fields only used in MLC
repetition_penalty: number;
// Fields shared by MLC and OpenAI APIs
frequency_penalty: number;
presence_penalty: number;
top_p: number;
temperature: number;
bos_token_id?: number;
// Model type identifier from mlc-chat-config.json (e.g. "phi3_v", "gemma3_v")
model_type?: string;
// Nested model config from mlc-chat-config.json, contains model-specific parameters
model_config?: VisionModelConfig & Record<string, unknown>;
}
/**
* Custom options that can be used to override known config values.
*/
// eslint-disable-next-line @typescript-eslint/no-empty-object-type
export interface ChatOptions extends Partial<ChatConfig> {}
/**
* Optional configurations for `CreateMLCEngine()` and `CreateWebWorkerMLCEngine()`.
*
* appConfig: Configure the app, including model list and persistent cache backend.
* initProgressCallback: A callback for showing the progress of loading the model.
* logitProcessorRegistry: A register for stateful logit processors, see `webllm.LogitProcessor`.
*
* @note All fields are optional, and `logitProcessorRegistry` is only used for `MLCEngine` and not
* other `MLCEngine`s.
*/
export interface MLCEngineConfig {
appConfig?: AppConfig;
initProgressCallback?: InitProgressCallback;
logitProcessorRegistry?: Map<string, LogitProcessor>;
logLevel?: LogLevel;
}
/**
* Config for a single generation.
* Essentially `ChatConfig` without `tokenizer_files`, `conv_config`, or `conv_template`.
* We also support additional fields not present in `mlc-chat-config.json` due to OpenAI-like APIs.
*
* Note that all values are optional. If unspecified, we use whatever values in `ChatConfig`
* initialized during `MLCEngine.reload()`.
* Values with numeric range checks also reject `NaN`.
*/
export interface GenerationConfig {
// Only used in MLC
repetition_penalty?: number | null;
ignore_eos?: boolean;
// Shared by MLC and OpenAI APIs
top_p?: number | null;
temperature?: number | null;
// Only in OpenAI APIs
max_tokens?: number | null;
frequency_penalty?: number | null;
presence_penalty?: number | null;
stop?: string | null | Array<string>;
n?: number | null;
logit_bias?: Record<string, number> | null;
logprobs?: boolean | null;
top_logprobs?: number | null;
response_format?: ResponseFormat | null;
// extra_body in ChatCompletionsRequest
enable_thinking?: boolean | null;
enable_latency_breakdown?: boolean | null;
}
export function postInitAndCheckGenerationConfigValues(
config: GenerationConfig,
): void {
function _hasValue(value: any): boolean {
// if we use `if value` directly, `value` being 0 evaluates to false, violating semantics
return value !== undefined && value !== null;
}
if (
_hasValue(config.frequency_penalty) &&
!(config.frequency_penalty! >= -2.0 && config.frequency_penalty! <= 2.0)
) {
throw new RangeError("frequency_penalty", -2.0, 2.0);
}
if (
_hasValue(config.presence_penalty) &&
!(config.presence_penalty! >= -2.0 && config.presence_penalty! <= 2.0)
) {
throw new RangeError("presence_penalty", -2.0, 2.0);
}
if (
_hasValue(config.repetition_penalty) &&
!(config.repetition_penalty! > 0)
) {
throw new MinValueError("repetition_penalty", 0);
}
if (_hasValue(config.max_tokens) && !(config.max_tokens! > 0)) {
throw new MinValueError("max_tokens", 0);
}
if (_hasValue(config.top_p) && !(config.top_p! > 0 && config.top_p! <= 1)) {
throw new RangeError("top_p", 0, 1);
}
if (_hasValue(config.temperature) && !(config.temperature! >= 0)) {
throw new NonNegativeError("temperature");
}
// If only one of frequency or presence penatly is set, make the other one 0.0
if (
_hasValue(config.frequency_penalty) &&
!_hasValue(config.presence_penalty)
) {
config.presence_penalty = 0.0;
log.warn("Only frequency_penalty is set; we default presence_penaty to 0.");
}
if (
_hasValue(config.presence_penalty) &&
!_hasValue(config.frequency_penalty)
) {
config.frequency_penalty = 0.0;
log.warn(
"Only presence_penalty is set; we default frequency_penalty to 0.",
);
}
// Check logit_bias range
if (_hasValue(config.logit_bias)) {
for (const tokenID in config.logit_bias) {
const bias = config.logit_bias[tokenID];
if (!(bias >= -100 && bias <= 100)) {
throw new RangeError(
"logit_bias",
-100,
100,
"Got " + bias + " for tokenID " + tokenID,
);
}
if (isNaN(parseInt(tokenID))) {
throw new InvalidNumberStringError("logit_bias's keys", tokenID);
}
}
}
// logprobs and top_logprobs
if (_hasValue(config.top_logprobs)) {
// If top_logprobs is non-null, logprobs must be true
if (!config.logprobs) {
throw new DependencyError("top_logprobs", "logprobs", true);
}
// top_logprobs should be in range [0,5]
if (!(config.top_logprobs! >= 0 && config.top_logprobs! <= 5)) {
throw new RangeError("top_logprobs", 0, 5, "Got " + config.top_logprobs);
}
}
// If defined logprobs but not top_logprobs, simply make it 0
if (config.logprobs) {
if (!_hasValue(config.top_logprobs)) {
config.top_logprobs = 0;
}
}
}
export enum ModelType {
"LLM",
"embedding",
"VLM", // vision-language model
}
/**
* Information for a model.
* @param model: the huggingface link to download the model weights, accepting four formats:
* - https://huggingface.co/{USERNAME}/{MODEL}, which we automatically use the main branch
* - https://huggingface.co/{USERNAME}/{MODEL}/, which we automatically use the main branch
* - https://huggingface.co/{USERNAME}/{MODEL}/resolve/{BRANCH}
* - https://huggingface.co/{USERNAME}/{MODEL}/resolve/{BRANCH}/
* @param model_id: what we call the model.
* @param model_lib: link to the model library (wasm file) the model uses.
* @param overrides: partial ChatConfig to override mlc-chat-config.json; can be used to change KVCache settings.
* @param vram_required_MB: amount of vram in MB required to run the model (can use
* `utils/vram_requirements` to calculate).
* @param low_resource_required: whether the model can run on limited devices (e.g. Android phone).
* @param buffer_size_required_bytes: required `maxStorageBufferBindingSize`, different for each device.
* @param required_features: feature needed to run this model (e.g. shader-f16).
* @param model_type: the intended usecase for the model, if unspecified, default to LLM.
* @param integrity: optional SRI hashes to verify downloaded artifacts. See {@link ModelIntegrity}.
* @param model_manifest: URL of mlc-model-manifest.json, relative to the model URL. The model
* is loaded through its manifest only when this is set.
*/
export interface ModelRecord {
model: string;
model_id: string;
model_lib: string;
overrides?: ChatOptions;
vram_required_MB?: number;
low_resource_required?: boolean;
buffer_size_required_bytes?: number;
required_features?: Array<string>;
model_type?: ModelType;
integrity?: ModelIntegrity;
model_manifest?: string;
}
/**
* Extra configuration that can be
* passed to the load.
*
* @param model_list: models to be used.
* @param cacheBackend: the backend to use for caching models and other artifacts.
* If unspecified, will use the Cache API. For more information, see:
* https://developer.mozilla.org/en-US/docs/Web/API/Storage_API/Storage_quotas_and_eviction_criteria#what_technologies_store_data_in_the_browser
* Supported values are:
* - "cache": browser Cache API.
* - "indexeddb": IndexedDB-backed cache.
* - "cross-origin": Chrome Cross-Origin Storage extension-backed cache.
* - "opfs": Origin Private File System-backed cache.
*
* @param opfsAccessMode: optional OPFS access mode. Only used when cacheBackend
* is "opfs".
* - "async": use async OPFS file APIs. This is the default.
* - "sync": require OPFS sync access handles.
* - "auto": use sync access handles when available and fall back to async OPFS otherwise.
*
* @note Note that the Cache API is the most well-tested in WebLLM as of now.
*/
export type CacheBackend = "cache" | "indexeddb" | "cross-origin" | "opfs";
export type OPFSAccessMode = "async" | "sync" | "auto";
export interface AppConfig {
model_list: Array<ModelRecord>;
cacheBackend?: CacheBackend;
opfsAccessMode?: OPFSAccessMode;
}
export function getCacheBackend(appConfig: AppConfig): CacheBackend {
if (appConfig.cacheBackend !== undefined) {
return appConfig.cacheBackend;
}
return "cache";
}
/**
* modelVersion: the prebuilt model libraries that the current npm is compatible with, affects the
* `model_lib`s in `prebuiltAppConfig`.
*
* @note The model version does not have to match the npm version, since not each npm update
* requires an update of the model libraries.
*/
export const modelVersion = "v0_2_86/base";
export const modelLibURLPrefix =
"https://raw.githubusercontent.com/mlc-ai/binary-mlc-llm-libs/main/web-llm-models/";
/**
* Models that support function calling (i.e. usage of `ChatCompletionRequest.tools`). More to come.
*/
export const functionCallingModelIds = [
"Hermes-2-Pro-Llama-3-8B-q4f16_1-MLC",
"Hermes-2-Pro-Llama-3-8B-q4f32_1-MLC",
"Hermes-2-Pro-Mistral-7B-q4f16_1-MLC",
"Hermes-3-Llama-3.1-8B-q4f32_1-MLC",
"Hermes-3-Llama-3.1-8B-q4f16_1-MLC",
];
/**
* Default models and model library mapping to be used if unspecified.
*
* @note This is the only source of truth of which prebuilt model libraries are compatible with the
* current WebLLM npm version.
*/
export const prebuiltAppConfig: AppConfig = {
cacheBackend: "cache",
model_list: [
// Llama-3.2
{
model: "https://huggingface.co/mlc-ai/Llama-3.2-1B-Instruct-q4f32_1-MLC",
model_id: "Llama-3.2-1B-Instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-1B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 1128.82,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.2-1B-Instruct-q4f16_1-MLC",
model_id: "Llama-3.2-1B-Instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-1B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 879.04,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.2-1B-Instruct-q0f32-MLC",
model_id: "Llama-3.2-1B-Instruct-q0f32-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-1B-Instruct-q0f32_cs1k-webgpu.wasm",
vram_required_MB: 5106.26,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.2-1B-Instruct-q0f16-MLC",
model_id: "Llama-3.2-1B-Instruct-q0f16-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-1B-Instruct-q0f16_cs1k-webgpu.wasm",
vram_required_MB: 2573.13,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.2-3B-Instruct-q4f32_1-MLC",
model_id: "Llama-3.2-3B-Instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-3B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 2951.51,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.2-3B-Instruct-q4f16_1-MLC",
model_id: "Llama-3.2-3B-Instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-3B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 2263.69,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
// Llama-3.1
{
model: "https://huggingface.co/mlc-ai/Llama-3.1-8B-Instruct-q4f32_1-MLC",
model_id: "Llama-3.1-8B-Instruct-q4f32_1-MLC-1k",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 5295.7,
low_resource_required: true,
overrides: {
context_window_size: 1024,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.1-8B-Instruct-q4f16_1-MLC",
model_id: "Llama-3.1-8B-Instruct-q4f16_1-MLC-1k",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4598.34,
low_resource_required: true,
overrides: {
context_window_size: 1024,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.1-8B-Instruct-q4f32_1-MLC",
model_id: "Llama-3.1-8B-Instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 6101.01,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Llama-3.1-8B-Instruct-q4f16_1-MLC",
model_id: "Llama-3.1-8B-Instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 5001.0,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
// DeepSeek-R1-Distill-Qwen
// TODO(Charlie): Qwen2-1.5B is experiencing correctness issue, hence commented for now.
// {
// model: "https://huggingface.co/mlc-ai/DeepSeek-R1-Distill-Qwen-1.5B-q4f16_1-MLC",
// model_id: "DeepSeek-R1-Distill-Qwen-1.5B-q4f16_1-MLC",
// model_lib:
// modelLibURLPrefix +
// modelVersion +
// "/Qwen2-1.5B-Instruct-q4f16_1_cs1k-webgpu.wasm",
// low_resource_required: true,
// vram_required_MB: 1629.75,
// overrides: {
// context_window_size: 4096,
// },
// },
// {
// model: "https://huggingface.co/mlc-ai/DeepSeek-R1-Distill-Qwen-1.5B-q4f32_1-MLC",
// model_id: "DeepSeek-R1-Distill-Qwen-1.5B-q4f32_1-MLC",
// model_lib:
// modelLibURLPrefix +
// modelVersion +
// "/Qwen2-1.5B-Instruct-q4f32_1_cs1k-webgpu.wasm",
// low_resource_required: true,
// vram_required_MB: 1888.97,
// overrides: {
// context_window_size: 4096,
// },
// },
{
model:
"https://huggingface.co/mlc-ai/DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC",
model_id: "DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Qwen2-7B-Instruct-q4f16_1_cs1k-webgpu.wasm",
low_resource_required: false,
vram_required_MB: 5106.67,
overrides: {
context_window_size: 4096,
},
},
{
model:
"https://huggingface.co/mlc-ai/DeepSeek-R1-Distill-Qwen-7B-q4f32_1-MLC",
model_id: "DeepSeek-R1-Distill-Qwen-7B-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Qwen2-7B-Instruct-q4f32_1_cs1k-webgpu.wasm",
low_resource_required: false,
vram_required_MB: 5900.09,
overrides: {
context_window_size: 4096,
},
},
// DeepSeek-R1-Distill-Llama
{
model:
"https://huggingface.co/mlc-ai/DeepSeek-R1-Distill-Llama-8B-q4f32_1-MLC",
model_id: "DeepSeek-R1-Distill-Llama-8B-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 6101.01,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model:
"https://huggingface.co/mlc-ai/DeepSeek-R1-Distill-Llama-8B-q4f16_1-MLC",
model_id: "DeepSeek-R1-Distill-Llama-8B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 5001.0,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
// Hermes-3 and Hermes-2
{
model:
"https://huggingface.co/mlc-ai/Hermes-2-Theta-Llama-3-8B-q4f16_1-MLC",
model_id: "Hermes-2-Theta-Llama-3-8B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3-8B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4976.13,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model:
"https://huggingface.co/mlc-ai/Hermes-2-Theta-Llama-3-8B-q4f32_1-MLC",
model_id: "Hermes-2-Theta-Llama-3-8B-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3-8B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 6051.27,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model:
"https://huggingface.co/mlc-ai/Hermes-2-Pro-Llama-3-8B-q4f16_1-MLC",
model_id: "Hermes-2-Pro-Llama-3-8B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3-8B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4976.13,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model:
"https://huggingface.co/mlc-ai/Hermes-2-Pro-Llama-3-8B-q4f32_1-MLC",
model_id: "Hermes-2-Pro-Llama-3-8B-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3-8B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 6051.27,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Hermes-3-Llama-3.2-3B-q4f32_1-MLC",
model_id: "Hermes-3-Llama-3.2-3B-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-3B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 2951.51,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Hermes-3-Llama-3.2-3B-q4f16_1-MLC",
model_id: "Hermes-3-Llama-3.2-3B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3.2-3B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 2263.69,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Hermes-3-Llama-3.1-8B-q4f32_1-MLC",
model_id: "Hermes-3-Llama-3.1-8B-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 5779.27,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Hermes-3-Llama-3.1-8B-q4f16_1-MLC",
model_id: "Hermes-3-Llama-3.1-8B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Llama-3_1-8B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4876.13,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model:
"https://huggingface.co/mlc-ai/Hermes-2-Pro-Mistral-7B-q4f16_1-MLC",
model_id: "Hermes-2-Pro-Mistral-7B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4033.28,
low_resource_required: false,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
// Phi-3.5-mini-instruct
{
model: "https://huggingface.co/mlc-ai/Phi-3.5-mini-instruct-q4f16_1-MLC",
model_id: "Phi-3.5-mini-instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-3.5-mini-instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 3672.07,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Phi-3.5-mini-instruct-q4f32_1-MLC",
model_id: "Phi-3.5-mini-instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-3.5-mini-instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 5483.12,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Phi-3.5-mini-instruct-q4f16_1-MLC",
model_id: "Phi-3.5-mini-instruct-q4f16_1-MLC-1k",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-3.5-mini-instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 2520.07,
low_resource_required: true,
overrides: {
context_window_size: 1024,
},
},
{
model: "https://huggingface.co/mlc-ai/Phi-3.5-mini-instruct-q4f32_1-MLC",
model_id: "Phi-3.5-mini-instruct-q4f32_1-MLC-1k",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-3.5-mini-instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 3179.12,
low_resource_required: true,
overrides: {
context_window_size: 1024,
},
},
// Phi-3.5-vision-instruct
{
model:
"https://huggingface.co/mlc-ai/Phi-3.5-vision-instruct-q4f16_1-MLC",
model_id: "Phi-3.5-vision-instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-3.5-vision-instruct-q4f16_1_cs4k-webgpu.wasm",
vram_required_MB: 4521.54,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
model_type: ModelType.VLM,
},
{
model:
"https://huggingface.co/mlc-ai/Phi-3.5-vision-instruct-q4f32_1-MLC",
model_id: "Phi-3.5-vision-instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-3.5-vision-instruct-q4f32_1_cs4k-webgpu.wasm",
vram_required_MB: 7050.65,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
model_type: ModelType.VLM,
},
// Phi-4-mini-instruct
{
model: "https://huggingface.co/mlc-ai/Phi-4-mini-instruct-q4f16_1-MLC",
model_id: "Phi-4-mini-instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-4-mini-instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 3437.58,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/Phi-4-mini-instruct-q4f32_1-MLC",
model_id: "Phi-4-mini-instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Phi-4-mini-instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 4220.59,
low_resource_required: false,
overrides: {
context_window_size: 4096,
},
},
// Mistral variants
{
model:
"https://huggingface.co/mlc-ai/Mistral-7B-Instruct-v0.3-q4f16_1-MLC",
model_id: "Mistral-7B-Instruct-v0.3-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4573.39,
low_resource_required: false,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
{
model:
"https://huggingface.co/mlc-ai/Mistral-7B-Instruct-v0.3-q4f32_1-MLC",
model_id: "Mistral-7B-Instruct-v0.3-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 5619.27,
low_resource_required: false,
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
{
model:
"https://huggingface.co/mlc-ai/Mistral-7B-Instruct-v0.2-q4f16_1-MLC",
model_id: "Mistral-7B-Instruct-v0.2-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4573.39,
low_resource_required: false,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
{
model:
"https://huggingface.co/mlc-ai/OpenHermes-2.5-Mistral-7B-q4f16_1-MLC",
model_id: "OpenHermes-2.5-Mistral-7B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4573.39,
low_resource_required: false,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
{
model:
"https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC",
model_id: "NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4573.39,
low_resource_required: false,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
{
model: "https://huggingface.co/mlc-ai/WizardMath-7B-V1.1-q4f16_1-MLC",
model_id: "WizardMath-7B-V1.1-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/Mistral-7B-Instruct-v0.3-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 4573.39,
low_resource_required: false,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
sliding_window_size: -1,
},
},
// SmolLM2
{
model: "https://huggingface.co/mlc-ai/SmolLM2-1.7B-Instruct-q4f16_1-MLC",
model_id: "SmolLM2-1.7B-Instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/SmolLM2-1.7B-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 1774.19,
low_resource_required: true,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/SmolLM2-1.7B-Instruct-q4f32_1-MLC",
model_id: "SmolLM2-1.7B-Instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/SmolLM2-1.7B-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 2692.38,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/SmolLM2-360M-Instruct-q0f16-MLC",
model_id: "SmolLM2-360M-Instruct-q0f16-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/SmolLM2-360M-Instruct-q0f16_cs1k-webgpu.wasm",
vram_required_MB: 871.99,
low_resource_required: true,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/SmolLM2-360M-Instruct-q0f32-MLC",
model_id: "SmolLM2-360M-Instruct-q0f32-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/SmolLM2-360M-Instruct-q0f32_cs1k-webgpu.wasm",
vram_required_MB: 1743.99,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/SmolLM2-360M-Instruct-q4f16_1-MLC",
model_id: "SmolLM2-360M-Instruct-q4f16_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/SmolLM2-360M-Instruct-q4f16_1_cs1k-webgpu.wasm",
vram_required_MB: 376.06,
low_resource_required: true,
required_features: ["shader-f16"],
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/SmolLM2-360M-Instruct-q4f32_1-MLC",
model_id: "SmolLM2-360M-Instruct-q4f32_1-MLC",
model_lib:
modelLibURLPrefix +
modelVersion +
"/SmolLM2-360M-Instruct-q4f32_1_cs1k-webgpu.wasm",
vram_required_MB: 579.61,
low_resource_required: true,
overrides: {
context_window_size: 4096,
},
},
{
model: "https://huggingface.co/mlc-ai/SmolLM2-135M-Instruct-q0f16-MLC",
model_id: "SmolLM2-135M-Instruct-q0f16-MLC",
model_lib:
modelLibURLPrefix +