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[inference] Dynamic inference provider mapping (#1173)
_"it should work" 😄_ Still a draft while huggingface-internal/moon-landing#12398 (internal) is been merged/deployed. Goal is to use the dynamic mapping, and default back to hardcoded model ids if necessary (for backward compatibility). I haven't tested anything for now and I left some todos to address: - [x] what to do with `status: "live" | "staging"` ? => raise a warning - [ ] we need to cache the `modelInfo` call (only do it once at runtime) - [ ] how to handle if model supports both `text-generation` and `conversational` - [ ] how to deal with `"hf-inference"` if no taskHints? (for now, I kept as before) - [ ] tests are flaky (requires server-side update) **EDIT:** made an update to preserve previous behavior with hardcoded mapping. Dynamic mapping from the hub takes precedence. --------- Co-authored-by: SBrandeis <[email protected]> Co-authored-by: Julien Chaumond <[email protected]>
1 parent 671d03a commit 38d13dd

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-289
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‎packages/hub/src/lib/list-models.ts‎

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@@ -25,6 +25,7 @@ export const MODEL_EXPANDABLE_KEYS = [
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"downloadsAllTime",
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"gated",
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"gitalyUid",
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"inferenceProviderMapping",
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"lastModified",
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"library_name",
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"likes",

‎packages/hub/src/types/api/api-model.ts‎

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@@ -1,4 +1,4 @@
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import type { ModelLibraryKey, TransformersInfo } from "@huggingface/tasks";
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import type { ModelLibraryKey, TransformersInfo, WidgetType } from "@huggingface/tasks";
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import type { License, PipelineType } from "../public";
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export interface ApiModelInfo {
@@ -18,6 +18,9 @@ export interface ApiModelInfo {
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downloadsAllTime: number;
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files: string[];
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gitalyUid: string;
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inferenceProviderMapping: Partial<
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Record<string, { providerId: string; status: "live" | "staging"; task: WidgetType }>
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>;
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lastAuthor: { email: string; user?: string };
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lastModified: string; // convert to date
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library_name?: ModelLibraryKey;

‎packages/inference/src/index.ts‎

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@@ -1,9 +1,4 @@
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export type { ProviderMapping } from "./providers/types";
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export { HfInference, HfInferenceEndpoint } from "./HfInference";
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export { InferenceOutputError } from "./lib/InferenceOutputError";
4-
export { FAL_AI_SUPPORTED_MODEL_IDS } from "./providers/fal-ai";
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export { REPLICATE_SUPPORTED_MODEL_IDS } from "./providers/replicate";
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export { SAMBANOVA_SUPPORTED_MODEL_IDS } from "./providers/sambanova";
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export { TOGETHER_SUPPORTED_MODEL_IDS } from "./providers/together";
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export * from "./types";
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export * from "./tasks";

‎packages/inference/src/lib/getProviderModelId.ts‎

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import type { WidgetType } from "@huggingface/tasks";
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import type { InferenceProvider, InferenceTask, ModelId, Options, RequestArgs } from "../types";
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import { HF_HUB_URL } from "../config";
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import { HARDCODED_MODEL_ID_MAPPING } from "../providers/consts";
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type InferenceProviderMapping = Partial<
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Record<InferenceProvider, { providerId: string; status: "live" | "staging"; task: WidgetType }>
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>;
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const inferenceProviderMappingCache = new Map<ModelId, InferenceProviderMapping>();
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export async function getProviderModelId(
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params: {
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model: string;
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provider: InferenceProvider;
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},
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args: RequestArgs,
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options: {
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taskHint?: InferenceTask;
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chatCompletion?: boolean;
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fetch?: Options["fetch"];
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} = {}
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): Promise<string> {
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if (params.provider === "hf-inference") {
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return params.model;
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}
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if (!options.taskHint) {
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throw new Error("taskHint must be specified when using a third-party provider");
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}
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const task: WidgetType =
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options.taskHint === "text-generation" && options.chatCompletion ? "conversational" : options.taskHint;
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// A dict called HARDCODED_MODEL_ID_MAPPING takes precedence in all cases (useful for dev purposes)
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if (HARDCODED_MODEL_ID_MAPPING[params.model]) {
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return HARDCODED_MODEL_ID_MAPPING[params.model];
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}
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let inferenceProviderMapping: InferenceProviderMapping | null;
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if (inferenceProviderMappingCache.has(params.model)) {
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// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
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inferenceProviderMapping = inferenceProviderMappingCache.get(params.model)!;
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} else {
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inferenceProviderMapping = await (options?.fetch ?? fetch)(
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`${HF_HUB_URL}/api/models/${params.model}?expand[]=inferenceProviderMapping`,
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{
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headers: args.accessToken?.startsWith("hf_") ? { Authorization: `Bearer ${args.accessToken}` } : {},
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}
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)
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.then((resp) => resp.json())
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.then((json) => json.inferenceProviderMapping)
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.catch(() => null);
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}
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if (!inferenceProviderMapping) {
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throw new Error(`We have not been able to find inference provider information for model ${params.model}.`);
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}
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const providerMapping = inferenceProviderMapping[params.provider];
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if (providerMapping) {
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if (providerMapping.task !== task) {
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throw new Error(
61+
`Model ${params.model} is not supported for task ${task} and provider ${params.provider}. Supported task: ${providerMapping.task}.`
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);
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}
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if (providerMapping.status === "staging") {
65+
console.warn(
66+
`Model ${params.model} is in staging mode for provider ${params.provider}. Meant for test purposes only.`
67+
);
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}
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// TODO: how is it handled server-side if model has multiple tasks (e.g. `text-generation` + `conversational`)?
70+
return providerMapping.providerId;
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}
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throw new Error(`Model ${params.model} is not supported provider ${params.provider}.`);
74+
}

‎packages/inference/src/lib/makeRequestOptions.ts‎

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@@ -1,13 +1,13 @@
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import type { WidgetType } from "@huggingface/tasks";
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import { HF_HUB_URL } from "../config";
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import { FAL_AI_API_BASE_URL, FAL_AI_SUPPORTED_MODEL_IDS } from "../providers/fal-ai";
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import { REPLICATE_API_BASE_URL, REPLICATE_SUPPORTED_MODEL_IDS } from "../providers/replicate";
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import { SAMBANOVA_API_BASE_URL, SAMBANOVA_SUPPORTED_MODEL_IDS } from "../providers/sambanova";
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import { TOGETHER_API_BASE_URL, TOGETHER_SUPPORTED_MODEL_IDS } from "../providers/together";
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import { FAL_AI_API_BASE_URL } from "../providers/fal-ai";
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import { REPLICATE_API_BASE_URL } from "../providers/replicate";
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import { SAMBANOVA_API_BASE_URL } from "../providers/sambanova";
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import { TOGETHER_API_BASE_URL } from "../providers/together";
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import type { InferenceProvider } from "../types";
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import type { InferenceTask, Options, RequestArgs } from "../types";
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import { isUrl } from "./isUrl";
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import { version as packageVersion, name as packageName } from "../../package.json";
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import { getProviderModelId } from "./getProviderModelId";
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const HF_HUB_INFERENCE_PROXY_TEMPLATE = `${HF_HUB_URL}/api/inference-proxy/{{PROVIDER}}`;
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@@ -49,18 +49,16 @@ export async function makeRequestOptions(
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if (maybeModel && isUrl(maybeModel)) {
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throw new Error(`Model URLs are no longer supported. Use endpointUrl instead.`);
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}
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let model: string;
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if (!maybeModel) {
55-
if (taskHint) {
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model = mapModel({ model: await loadDefaultModel(taskHint), provider, taskHint, chatCompletion });
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} else {
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throw new Error("No model provided, and no default model found for this task");
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/// TODO : change error message ^
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}
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} else {
62-
model = mapModel({ model: maybeModel, provider, taskHint, chatCompletion });
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if (!maybeModel && !taskHint) {
53+
throw new Error("No model provided, and no task has been specified.");
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}
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// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
56+
const hfModel = maybeModel ?? (await loadDefaultModel(taskHint!));
57+
const model = await getProviderModelId({ model: hfModel, provider }, args, {
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taskHint,
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chatCompletion,
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fetch: options?.fetch,
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});
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6563
/// If accessToken is passed, it should take precedence over includeCredentials
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const authMethod = accessToken
@@ -153,39 +151,6 @@ export async function makeRequestOptions(
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return { url, info };
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}
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156-
function mapModel(params: {
157-
model: string;
158-
provider: InferenceProvider;
159-
taskHint: InferenceTask | undefined;
160-
chatCompletion: boolean | undefined;
161-
}): string {
162-
if (params.provider === "hf-inference") {
163-
return params.model;
164-
}
165-
if (!params.taskHint) {
166-
throw new Error("taskHint must be specified when using a third-party provider");
167-
}
168-
const task: WidgetType =
169-
params.taskHint === "text-generation" && params.chatCompletion ? "conversational" : params.taskHint;
170-
const model = (() => {
171-
switch (params.provider) {
172-
case "fal-ai":
173-
return FAL_AI_SUPPORTED_MODEL_IDS[task]?.[params.model];
174-
case "replicate":
175-
return REPLICATE_SUPPORTED_MODEL_IDS[task]?.[params.model];
176-
case "sambanova":
177-
return SAMBANOVA_SUPPORTED_MODEL_IDS[task]?.[params.model];
178-
case "together":
179-
return TOGETHER_SUPPORTED_MODEL_IDS[task]?.[params.model];
180-
}
181-
})();
182-
183-
if (!model) {
184-
throw new Error(`Model ${params.model} is not supported for task ${task} and provider ${params.provider}`);
185-
}
186-
return model;
187-
}
188-
189154
function makeUrl(params: {
190155
authMethod: "none" | "hf-token" | "credentials-include" | "provider-key";
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chatCompletion: boolean;

‎packages/inference/src/providers/consts.ts‎

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import type { ModelId } from "../types";
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type ProviderId = string;
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/**
6+
* If you want to try to run inference for a new model locally before it's registered on huggingface.co
7+
* for a given Inference Provider,
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* you can add it to the following dictionary, for dev purposes.
9+
*/
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export const HARDCODED_MODEL_ID_MAPPING: Record<ModelId, ProviderId> = {
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/**
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* "HF model ID" => "Model ID on Inference Provider's side"
13+
*/
14+
// "Qwen/Qwen2.5-Coder-32B-Instruct": "Qwen2.5-Coder-32B-Instruct",
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};

‎packages/inference/src/providers/fal-ai.ts‎

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import type { ProviderMapping } from "./types";
2-
31
export const FAL_AI_API_BASE_URL = "https://fal.run";
42

5-
type FalAiId = string;
6-
7-
export const FAL_AI_SUPPORTED_MODEL_IDS: ProviderMapping<FalAiId> = {
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"text-to-image": {
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"black-forest-labs/FLUX.1-schnell": "fal-ai/flux/schnell",
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"black-forest-labs/FLUX.1-dev": "fal-ai/flux/dev",
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"playgroundai/playground-v2.5-1024px-aesthetic": "fal-ai/playground-v25",
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"ByteDance/SDXL-Lightning": "fal-ai/lightning-models",
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"PixArt-alpha/PixArt-Sigma-XL-2-1024-MS": "fal-ai/pixart-sigma",
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"stabilityai/stable-diffusion-3-medium": "fal-ai/stable-diffusion-v3-medium",
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"Warlord-K/Sana-1024": "fal-ai/sana",
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"fal/AuraFlow-v0.2": "fal-ai/aura-flow",
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"stabilityai/stable-diffusion-xl-base-1.0": "fal-ai/fast-sdxl",
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"stabilityai/stable-diffusion-3.5-large": "fal-ai/stable-diffusion-v35-large",
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"stabilityai/stable-diffusion-3.5-large-turbo": "fal-ai/stable-diffusion-v35-large/turbo",
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"stabilityai/stable-diffusion-3.5-medium": "fal-ai/stable-diffusion-v35-medium",
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"Kwai-Kolors/Kolors": "fal-ai/kolors",
22-
},
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"automatic-speech-recognition": {
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"openai/whisper-large-v3": "fal-ai/whisper",
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},
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"text-to-video": {
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"genmo/mochi-1-preview": "fal-ai/mochi-v1",
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"tencent/HunyuanVideo": "fal-ai/hunyuan-video",
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"THUDM/CogVideoX-5b": "fal-ai/cogvideox-5b",
30-
"Lightricks/LTX-Video": "fal-ai/ltx-video",
31-
},
32-
};
3+
/**
4+
* See the registered mapping of HF model ID => Fal model ID here:
5+
*
6+
* https://huggingface.co/api/partners/fal-ai/models
7+
*
8+
* This is a publicly available mapping.
9+
*
10+
* If you want to try to run inference for a new model locally before it's registered on huggingface.co,
11+
* you can add it to the dictionary "HARDCODED_MODEL_ID_MAPPING" in consts.ts, for dev purposes.
12+
*
13+
* - If you work at Fal and want to update this mapping, please use the model mapping API we provide on huggingface.co
14+
* - If you're a community member and want to add a new supported HF model to Fal, please open an issue on the present repo
15+
* and we will tag Fal team members.
16+
*
17+
* Thanks!
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*/

‎packages/inference/src/providers/replicate.ts‎

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import type { ProviderMapping } from "./types";
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export const REPLICATE_API_BASE_URL = "https://api.replicate.com";
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5-
type ReplicateId = string;
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7-
export const REPLICATE_SUPPORTED_MODEL_IDS: ProviderMapping<ReplicateId> = {
8-
"text-to-image": {
9-
"black-forest-labs/FLUX.1-dev": "black-forest-labs/flux-dev",
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"black-forest-labs/FLUX.1-schnell": "black-forest-labs/flux-schnell",
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"ByteDance/Hyper-SD":
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"bytedance/hyper-flux-16step:382cf8959fb0f0d665b26e7e80b8d6dc3faaef1510f14ce017e8c732bb3d1eb7",
13-
"ByteDance/SDXL-Lightning":
14-
"bytedance/sdxl-lightning-4step:5599ed30703defd1d160a25a63321b4dec97101d98b4674bcc56e41f62f35637",
15-
"playgroundai/playground-v2.5-1024px-aesthetic":
16-
"playgroundai/playground-v2.5-1024px-aesthetic:a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24",
17-
"stabilityai/stable-diffusion-3.5-large-turbo": "stability-ai/stable-diffusion-3.5-large-turbo",
18-
"stabilityai/stable-diffusion-3.5-large": "stability-ai/stable-diffusion-3.5-large",
19-
"stabilityai/stable-diffusion-3.5-medium": "stability-ai/stable-diffusion-3.5-medium",
20-
"stabilityai/stable-diffusion-xl-base-1.0":
21-
"stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc",
22-
},
23-
"text-to-speech": {
24-
"OuteAI/OuteTTS-0.3-500M": "jbilcke/oute-tts:3c645149db020c85d080e2f8cfe482a0e68189a922cde964fa9e80fb179191f3",
25-
"hexgrad/Kokoro-82M": "jaaari/kokoro-82m:dfdf537ba482b029e0a761699e6f55e9162cfd159270bfe0e44857caa5f275a6",
26-
},
27-
"text-to-video": {
28-
"genmo/mochi-1-preview": "genmoai/mochi-1:1944af04d098ef69bed7f9d335d102e652203f268ec4aaa2d836f6217217e460",
29-
},
30-
};
3+
/**
4+
* See the registered mapping of HF model ID => Replicate model ID here:
5+
*
6+
* https://huggingface.co/api/partners/replicate/models
7+
*
8+
* This is a publicly available mapping.
9+
*
10+
* If you want to try to run inference for a new model locally before it's registered on huggingface.co,
11+
* you can add it to the dictionary "HARDCODED_MODEL_ID_MAPPING" in consts.ts, for dev purposes.
12+
*
13+
* - If you work at Replicate and want to update this mapping, please use the model mapping API we provide on huggingface.co
14+
* - If you're a community member and want to add a new supported HF model to Replicate, please open an issue on the present repo
15+
* and we will tag Replicate team members.
16+
*
17+
* Thanks!
18+
*/

‎packages/inference/src/providers/sambanova.ts‎

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1-
import type { ProviderMapping } from "./types";
2-
31
export const SAMBANOVA_API_BASE_URL = "https://api.sambanova.ai";
42

5-
type SambanovaId = string;
6-
7-
export const SAMBANOVA_SUPPORTED_MODEL_IDS: ProviderMapping<SambanovaId> = {
8-
/** Chat completion / conversational */
9-
conversational: {
10-
"allenai/Llama-3.1-Tulu-3-405B":"Llama-3.1-Tulu-3-405B",
11-
"deepseek-ai/DeepSeek-R1-Distill-Llama-70B": "DeepSeek-R1-Distill-Llama-70B",
12-
"Qwen/Qwen2.5-Coder-32B-Instruct": "Qwen2.5-Coder-32B-Instruct",
13-
"Qwen/Qwen2.5-72B-Instruct": "Qwen2.5-72B-Instruct",
14-
"Qwen/QwQ-32B-Preview": "QwQ-32B-Preview",
15-
"meta-llama/Llama-3.3-70B-Instruct": "Meta-Llama-3.3-70B-Instruct",
16-
"meta-llama/Llama-3.2-1B-Instruct": "Meta-Llama-3.2-1B-Instruct",
17-
"meta-llama/Llama-3.2-3B-Instruct": "Meta-Llama-3.2-3B-Instruct",
18-
"meta-llama/Llama-3.2-11B-Vision-Instruct": "Llama-3.2-11B-Vision-Instruct",
19-
"meta-llama/Llama-3.2-90B-Vision-Instruct": "Llama-3.2-90B-Vision-Instruct",
20-
"meta-llama/Llama-3.1-8B-Instruct": "Meta-Llama-3.1-8B-Instruct",
21-
"meta-llama/Llama-3.1-70B-Instruct": "Meta-Llama-3.1-70B-Instruct",
22-
"meta-llama/Llama-3.1-405B-Instruct": "Meta-Llama-3.1-405B-Instruct",
23-
"meta-llama/Llama-Guard-3-8B": "Meta-Llama-Guard-3-8B",
24-
},
25-
};
3+
/**
4+
* See the registered mapping of HF model ID => Sambanova model ID here:
5+
*
6+
* https://huggingface.co/api/partners/sambanova/models
7+
*
8+
* This is a publicly available mapping.
9+
*
10+
* If you want to try to run inference for a new model locally before it's registered on huggingface.co,
11+
* you can add it to the dictionary "HARDCODED_MODEL_ID_MAPPING" in consts.ts, for dev purposes.
12+
*
13+
* - If you work at Sambanova and want to update this mapping, please use the model mapping API we provide on huggingface.co
14+
* - If you're a community member and want to add a new supported HF model to Sambanova, please open an issue on the present repo
15+
* and we will tag Sambanova team members.
16+
*
17+
* Thanks!
18+
*/

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